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dc.contributor.authorBalcázar Navarro, José Luis
dc.contributor.authorTirnauca, Cristina
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics
dc.date.accessioned2013-02-11T15:24:34Z
dc.date.created2011
dc.date.issued2011
dc.identifier.citationBalcázar, J.; Tirnauca, Cristina. Border algorithms for computing Hasse diagrams of arbitrary lattices. A: International Conference on Formal Concept Analysis. "Formal Concept Analysis - 9th International Conference". Springer, 2011, p. 49-64.
dc.identifier.isbn978-3-642-20513-2
dc.identifier.urihttp://hdl.handle.net/2117/17639
dc.description.abstractLattices are mathematical structures with many applications in computer science; among these, we are interested in fields like data mining, machine learning, or knowledge discovery in databases. One well-established use of lattice theory is in formal concept analysis (FCA), where the concept lattice with its diagram graph allows the visualization and summarization of data in a more concise representation. In the Data Mining community, the same mathematical notions (often under additional “frequency” constraints that bound from below the size of the support set) are studied under the banner of Closed-Set Mining. In these applications, each dataset consists of transactions, also called objects, each of which, besides having received a unique identifier, consists of a set of items or attributes taken from a previously agreed finite set. A concept is a pair formed by a set of transactions —the extent set or support set of the concept— and a set of attributes —the intent set of the concept— defined as the set of all those attributes that are shared by all the transactions present in the extent. Some data analysis processes are based on the family of all intents (the “closures” stemming from the dataset); but others require to determine also their order relation, which is a finite lattice, in the form of a line graph (the Hasse diagram).
dc.format.extent16 p.
dc.language.isoeng
dc.publisherSpringer
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subject.lcshData mining
dc.subject.lcshKnowledge representation (Information theory)
dc.subject.otherLattices
dc.subject.otherHasse diagrams
dc.subject.otherBorder algorithms
dc.titleBorder algorithms for computing Hasse diagrams of arbitrary lattices
dc.typeConference report
dc.subject.lemacMineria de dades
dc.subject.lemacRepresentació del coneixement (Teoria de la informació)
dc.contributor.groupUniversitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge
dc.identifier.doi10.1007/978-3-642-20514-9_6
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.springerlink.com/content/h174152www287510/
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac9401607
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorBalcázar, J.; Tirnauca, Cristina
local.citation.contributorInternational Conference on Formal Concept Analysis
local.citation.publicationNameFormal Concept Analysis - 9th International Conference
local.citation.startingPage49
local.citation.endingPage64


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